Methods in Medical Informatics : Fundamentals of Healthcare Programming in Perl, Python, and Ruby (Paperback)

PART I FUNDAMENTAL ALGORITHMS AND METHODS OF MEDICAL INFORMATICSChapter 1 Parsing and Transforming Text FilesPeeking into Large FilesPaging through Large Text FilesExtracting Lines that Match a Regular ExpressionChanging Every File in a SubdirectoryCounting the Words in a FileMaking a Word List with Occurrence TallyUsing Printf Formatting StyleChapter 2 Utility ScriptsRandom NumbersConverting Non-ASCII to Base64 ASCIICreating a Universally Unique IdentifierSplitting Text into SentencesOne-Way Hash on a NameOne-Way Hash on a FileA Prime Number GeneratorChapter 3 Viewing and Modifying ImagesViewing a JPEG ImageConverting between Image FormatsBatch ConversionsDrawing a Graph from List DataDrawing an Image MashupChapter 4 Indexing TextZIPF Distribution of a Text FilePreparing a ConcordanceExtracting PhrasesPreparing an IndexComparing Texts Using Similarity ScoresPART II MEDICAL DATA RESOURCESChapter 5 The National Library of Medicine’s Medical Subject Headings (MeSH )Determining the Hierarchical Lineage for MeSH TermsCreating a MeSH DatabaseReading the MeSH DatabaseCreating an SQLite Database for MeSHReading the SQLite MeSH DatabaseChapter 6 The International Classification of DiseasesCreating the ICD DictionaryBuilding the ICD-O (Oncology) DictionaryChapter 7 SEER: The Cancer Surveillance, Epidemiology, and End Results ProgramParsing the SEER Data FilesFinding the Occurrences of All Cancers in the SEER Data FilesFinding the Age Distributions of the Cancers in the SEER Data FilesChapter 8 OMIM: The Online Mendelian Inheritance in ManCollecting the OMIM Entry TermsFinding Inherited Cancer ConditionsChapter 9 PubMedBuilding a Large Text Corpus of Biomedical InformationCreating a List of Doublets from a PubMed CorpusDownloading Gene Synonyms from PubMedDownloading Protein Synonyms from PubMedChapter 10 TaxonomyFinding a Taxonomic HierarchyFinding the Restricted Classes of Human Infectious PathogensChapter 11 Developmental Lineage Classification and Taxonomyof NeoplasmsBuilding the Doublet HashScanning the Literature for Candidate TermsAdding Terms to the Neoplasm ClassificationDetermining the Lineage of Every Neoplasm ConceptChapter 12 U.S. Census FilesTotal Population of the United StatesStratified Distribution for the U.S. CensusAdjusting for AgeChapter 13 Centers for Disease Control and Prevention Mortality FilesDeath Certificate DataObtaining the CDC Data FilesHow Death Certificates Are Represented in Data RecordsRanking, by Number of Occurrences, Every Condition in the CDCMortality FilesPART III PRIMARY TASKS OF MEDICAL INFORMATICSChapter 14 AutocodingA Neoplasm AutocoderRecodingChapter 15 Text Scrubber for Deidentifyin g Confidential TextChapter 16 Web Pages and CGI ScriptsGrabbing Web PagesCGI Script for Searching the Neoplasm ClassificationChapter 17 Image AnnotationInserting a Header CommentExtracting the Header Comment in a JPEG Image FileInserting IPTC AnnotationsExtracting Comment, EXIF, and IPTC AnnotationsDealing with DICOMFinding DICOM ImagesDICOM-to-JPEG ConversionChapter 18 Describing Data with Data, Using XMLParsing XMLResource Description Framework (RDF)Dublin Core MetadataInsert an RDF Document into an Image FileInsert an Image File into an RDF DocumentRDF SchemaVisualizing an RDF Schema with GraphVizObtaining GraphVizConverting a Data Structure to GraphVizPART IV MEDICAL DISCOVERYChapter 19 Case Study: Emphysema RatesChapter 20 Case Study: Cancer Occurrence RatesChapter 21 Case Study: Germ Cell Tumor Rates across EthnicitiesChapter 22 Case Study: Ranking the Death-Certifying Process, by StateChapter 23 Case Study: Data Mashups for EpidemicsTally of Coccidioidomycosis Cases by StateCreating the Map MashupChapter 24 Case Study: Sickle Cell RatesChapter 25 Case Study: Site-Specific Tumor BiologyAnatomic Origins of MesotheliomasMesothelioma Records in the SEER Data SetsGraphic RepresentationChapter 26 Case Study: Bimodal TumorsChapter 27 Case Study: The Age of Occurrence of PrecancersEpilogue for Healthcare Professionals and Medical ScientistsLearn One or More Open Source Programming LanguagesDon’t Agonize Over Which Language You Should ChooseLearn AlgorithmsUnless You Are a Professional Programmer, Relax and Enjoy Being a NewbieDo Not Delegate Simple Programming Tasks to OthersBreak Complex Tasks into Simple Methods and AlgorithmsWrite Fast ScriptsConcentrate on the Questions, Not the AnswersAppendixHow to Acquire RubyHow to Acquire PerlHow to Acquire PythonHow to Acquire RMagickHow to Acquire SQLiteHow to Acquire the Public Data Files Used in This BookOther Publicly Available Files, Data Sets, and Utilities